Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 495 for “"AUC"”.
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Development of MWL-AUC / CCD-C-AUC / SLS-AUC detectors for the analytical ultracentrifuge
Analytical ultracentrifugation (AUC) has made an important contribution to polymer and particle characterization since its invention by Svedberg (Svedberg and Nichols 1923; Svedberg and Pederson 1940) in 1923. In 1926, Svedberg won the Nobel price for his scientific work on disperse systems …
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Assessing the impact of tablet crushing, dose, and high-calorie, high-fat meal on vericiguat absorption from the upper gastrointestinal lumen using standardized commercially available equipment and materials
… μετρηθεί στο παρελθόν. Αποτελέσματα: (〖Mean AUC〗_(Crushed Tablet 10mg)^(BioGIThighcal,colloidal,180min))/(Mean 〖AUC〗_(Tablet 10mg)^(BioGIThighcal,colloidal,180min ) )=1.04, (〖Mean AUC〗_(Crushed Tablet 10mg)^(BioGIThighcal,micellar,180min))/(〖Mean AUC〗_(Tablet …
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Exploration of cell-free DNA’s biological properties for better understanding and improved circulating tumour DNA detection
… obtained from previous publications) showed an AUC of 0.98, 0.94 and 0.99 in train (n=279), and 0.97, 0.86 and 0.96 in test (n=183) data from in-house sWGS plasma data (0.4X depth), with AUC of >0.97, >0.84 and >0.96 in early stage (stages I and II) disease and AUC of >0.99, >0.91 and >0.99in …
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Development of machine learning algorithms for screening of pulmonary disease
… demonstrated moderate performance with AUCs ranging from 0.87 to 0.90. As a second approach, a standalone classifier was also explored, which produced much better results, with an AUC of 0.96. Going forward, we plan to use an independent classifier as part of our diagnostics. In the …
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Predictive Modeling of Early Stage Parkinsons Disease
… PD from controls with > 80% cross-validated AUC, but that the diverse nature of SWEDD would reduce early PD versus SWEDD CV classification AUC and alter model-based rank of predictor importance among model types. Methods: Baseline data was acquired from the Parkinsons Progressive Markers …
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Early Stopping of a Neural Network via the Receiver Operating Curve.
… Operating Characteristics) curve, or abbreviated AUC, as an alternate measure for evaluating the predictive performance of ANNs (Artificial Neural Networks) classifiers. Conventionally, neural networks are trained to have total error converge to zero which may give rise to over-fitting problems. …
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Sample Size Formulas For Estimating Areas Under the Receiver Operating Characteristic Curves With Precision and Assurance
… the receiver operating characteristic curve (AUC) is commonly used to quantify the discriminative ability of tests with ordinal or continuous test data. When planning a study to evaluate a new test, it is important to determine a minimum sample size required to achieve a prespecified precision …
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Convolutional Neural Net Models and Image Processing Methods for Predicting Surgical Site Infection
… CNN models were constructed. The overall median AUC values for each model, based on the ROC curve, were as follows: Na¨ıve CNN for Dataset A (Median AUC = 0.65), Transfer learning CNN for Data A (Median AUC = 0.64), Na¨ıve CNN for Dataset B (Median AUC = 0.68), Transfer learning CNN for Data B …
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Detecting hazardous intensive care patient episodes using real-time mortality models
… ability for patient mortality, with an ROC area (AUC) of 0.880. The final model includes a number of variables known to be associated with mortality, but also computationally intensive variables absent in other severity scores. In addition to RAS, I also develop secondary outcome models that …
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Probing metal nanoparticles and assemblies with analytical ultracentrifugation
Analytical Ultracentrifugation (AUC) is a powerful tool to obtain statistically relevant size and shape measurements for macromolecular systems. Metal nanoparticles coated by a ligand shell of thiolated molecules provide diverse functionality, from targeted cellular delivery to the formation of …
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Improving Model Generalization of Pneumonia Detection from Chest Xray Images Using Deep Learning and Transfer Learning
… precision, recall, F1-score, error rate, and AUC-ROC, and further validated using an independent external dataset. Experimental results showed that DenseNet201 consistently outperformed ResNet152, reaching 93.2% accuracy with an AUC of 0.9916 on the main dataset and 88.3% accuracy with an AUC …
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Clinical and endocrine responses to ovarian hyperstimulation in flare and and luteal gonadotropin-releasing hormone agonist (GnRHa) protocols
… were evaluated by Area Under the Curve (AUC). Data were analyzed using the t-test and statistical significance was considered present at P<0.05. Results are reported as the mean ± SEM. Results: For flare versus luteal protocol, there was a significant difference in the number of total …
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The Effect of Physical Activity on the Insulin Response to Frequent Meals
… min for 12 h. Baseline and area under the curve (AUC) for serum glucose, insulin, c-peptide, total PYY concentrations, and subjective appetite ratings; as well as insulin pulsatility were determined. Results: No significant differences in baseline glucose, insulin or c-peptide concentrations …
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The use of ultrasound in the prediction of endometrial cancer in women with postmenopausal bleeding
… the receiver operating characteristics curve, AUC, 0.83), and the power Doppler ultrasound variable that best predicted malignancy was irregular branching of endometrial blood vessels (AUC 0.77). Mathematical models for evaluation of the individual risk of endometrial malignancy were …
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The Modified Rapid Emergency Medicine Score: A Novel Trauma Triaging Tool for Predicting In-hospital Mortality
… (ROC) curve. Results: The mREMS score (AUC 0.97) was demonstrated to be higher than RTS (AUC 0.96), ISS (AUC 0.78), MGAP (AUC 0.96), and SI (AUC 0.67) in predicting in-hospital mortality. Discussion: In the trauma population, mREMS is an accurate predictor of in-hospital mortality, …
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Gradient Boosted Decision Tree Application to Muon Identification in the KLM at Belle II
… This is seen in the lower Area Under the Curve (AUC) values for the FBDT ROC curves, achieving peak AUC values around 0.82, while the likelihood ratio ROC curves achieve peak AUC values around 0.98. Performance of the FBDT model in muon identification may be improved in the future by adding a …
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Evaluating the performance of the GRACE and TIMI risk scores in acute coronary syndromes: a South African cohort
… discrimination for in-hospital mortality (AUC=0.927, 95% CI: 0.83- 1.00 versus AUC=0.923, 95% CI: 0.87-0.98; p 0.91), and demonstrated modest accuracy for predicting 30-day mortality (GRACE AUC=0.587, 95% CI: 0.29-0.88; TIMI AUC=0.530, 95% CI: 0.12-0.94; p 0.44). In the NSTEMI cohort, GRACE …
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Neurologic And Metabolic Safety Of Fluoroquinolones
… of these models in a validation subset using AUC and calibration curves. For CNS dysfunction, LASSO had an AUC of 0.81 (95% CI: 0.80-0.82), while random forest had an AUC of 0.80 (95% CI: 0.80-0.81). For PNS dysfunction, LASSO had an AUC of 0.75 (95% CI: 0.74-0.76) vs. an AUC of 0.73 (95% CI: …
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Application of Advanced Bioanalytical Techniques to Studies of Oxaliplatin Chemotherapy
… under-the-plasma-concentration-versus-time-curve (AUC) from end-of-infusion plasma concentrations of intact oxaliplatin (AUC = 2.231*end-ofinfusion plasma concentration) and free platinum (AUC = 2.335*end-of-infusion plasma concentration). Together with other techniques, these AUC estimation …
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Localized customized mortality prediction modeling for patients with acute kidney injury admitted to the intensive care unit
… the Receiver Operating Characteristic Curve (AUC) and Hosmer-Lemeshow Goodness-of-Fit test (HL). The patient cohort was divided into a training and test data with a 70:30 split. Ten-fold cross-validation was performed on the training set for every combination of variables that were evaluated. …
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